| Autor: |
Habib, Maan, Habib, Ahed, Albzaie, Meshal, Farghal, Ali |
| Předmět: |
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| Zdroj: |
Discover Sustainability; 9/18/2024, Vol. 5 Issue 1, p1-21, 21p |
| Abstrakt: |
Infrastructure resilience is a critical issue in arid regions due to the unpredictability of extreme rainfall events influenced by climate change. Accordingly, the integration of artificial intelligence (AI) in engineering solutions to address such climatic challenges is important. This study aims to review AI-based engineering solutions for infrastructure resilience in arid areas against extreme rainfall and most importantly critically analyzes their sustainability benefits. By evaluating existing AI-based engineering solutions, this research highlights how these technologies can contribute to sustainable development goals (SDGs) and eventually aims to help set new standards in infrastructure resilience. The significance of this study lies in its potential to advance sustainable development goals by enhancing the resilience of critical infrastructure and equipping arid regions with innovative solutions to withstand adverse weather conditions. Expected outcomes of this study are anticipated to provide pivotal insights for policymakers, engineers, and urban planners, promoting the adoption of intelligent, sustainable infrastructure practices that are in line with global sustainability targets. Finally, this research promotes the adoption of AI solutions in infrastructure resilience and lays the groundwork for future explorations in this field. Highlights: AI solutions can improve infrastructure resilience and resource management in arid regions with extreme rainfall events. Using AI solutions in arid regions with extreme rainfall events aligns with SDGs for sustainable, resilient development. The study promotes working to develop cost-effective AI solutions for arid region resilience. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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Full text from SpringerLink